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Sensors 2015, 15(11), 28177-28192; doi:10.3390/s151128177

PMHT Approach for Multi-Target Multi-Sensor Sonar Tracking in Clutter

School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China
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Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 26 August 2015 / Revised: 18 October 2015 / Accepted: 2 November 2015 / Published: 6 November 2015
(This article belongs to the Section Physical Sensors)
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Abstract

Multi-sensor sonar tracking has many advantages, such as the potential to reduce the overall measurement uncertainty and the possibility to hide the receiver. However, the use of multi-target multi-sensor sonar tracking is challenging because of the complexity of the underwater environment, especially the low target detection probability and extremely large number of false alarms caused by reverberation. In this work, to solve the problem of multi-target multi-sensor sonar tracking in the presence of clutter, a novel probabilistic multi-hypothesis tracker (PMHT) approach based on the extended Kalman filter (EKF) and unscented Kalman filter (UKF) is proposed. The PMHT can efficiently handle the unknown measurements-to-targets and measurements-to-transmitters data association ambiguity. The EKF and UKF are used to deal with the high degree of nonlinearity in the measurement model. The simulation results show that the proposed algorithm can improve the target tracking performance in a cluttered environment greatly, and its computational load is low. View Full-Text
Keywords: probabilistic multi-hypothesis tracker (PMHT); multi-target multi-sensor sonar tracking; extended Kalman filter (EKF); unscented Kalman filter (UKF); data association probabilistic multi-hypothesis tracker (PMHT); multi-target multi-sensor sonar tracking; extended Kalman filter (EKF); unscented Kalman filter (UKF); data association
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Li, X.; Li, Y.; Yu, J.; Chen, X.; Dai, M. PMHT Approach for Multi-Target Multi-Sensor Sonar Tracking in Clutter. Sensors 2015, 15, 28177-28192.

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